Predictive Biomarkers of Response to Checkpoint Inhibitors in Triple Negative Breast Cancer: a Multiomics Platform

Recruiting

• Conditions: Triple Negative Breast Cancer
• Interventions: Diagnostic Test: Whole Genome Sequencing; Diagnostic Test: RNA-Sequencing; Diagnostic Test: Microbiome analysis; Diagnostic Test: ctDNA analysis; Diagnostic Test: TCR-β repertoire sequencing; Diagnostic Test: PBMCs phenotyping; Drug: Pembrolizumab; Drug: Chemotherapy

• Registration Number: NCT05916755
• Lead Sponsor: Vall d'Hebron Institute of Oncology

Brief Summary

Patients with stage II-III Triple negative breast cancer (TNBC) candidates to receive neoadjuvant chemotherapy (NACT) +/- immune checkpoint inhibitor (ICI) will be included. Several samples from different tissues will be analyzed through different omics to establish predictive biomarkers of response to the treatment. Multiple algorithms will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs in order to develop a clinical tool to assist clinicians in the process of treatment decision-making in TNBC.

Detailed Description

The combination of pembrolizumab, an immune checkpoint inhibitor (ICI), with neoadjuvant chemotherapy (NACT) increases pathologic complete response (pCR) and event-free survival (EFS) in patients with early triple negative breast cancer (eTNBC). However, not all patients equally benefit from a treatment that may have relevant adverse events (AEs).

Objectives: (1) To establish predictive biomarkers of response to NACT + ICI in eTNBC by correlating data coming from different layers of omics performed in different tissues, together with imaging, with pCR, EFS, and overall survival (OS). (2) To integrate data generated from (1), and clinical data, and explore multivariate predictive models of response to NACT + ICI.

Methods: Patients with stage II-III TNBC candidates to receive NACT +/- ICI will be included. Collected samples and type of analysis: (1) Tumor tissue (baseline and from residual disease after NACT): whole genome sequencing (WGS) and RNA-Seq will be performed (Hartwig sequencing platform and analytical pipeline), tissue immune phenotyping (PD-L1, T and B infiltrating lymphocytes, among others), and microbiome analysis (16S rRNA); (2) Blood (before and during NACT): circulating tumor DNA (ctDNA) analysis (targeted gene panel and shallow WGS), T-cell receptor beta (TCR-β) repertoire sequencing and analysis (ImmunoSeq hsTCRβ kit and immunoSEQ), and peripheral blood mononuclear cells (PBMCs) phenotyping; (3) Stools and saliva (before and during NACT): microbiome analysis (16S rRNA); (4) Breast MRI imaging (before and after NACT): radiomics analysis. Multiple algorithms including Multiple Kernel Learning, Multi-Omics Factor Analysis (MOFA) and Method for the Functional Integration of Spatial and Temporal Omics data (MEFISTO) will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs. The aim is to provide more personalized treatment efficacy and risk for relapse estimates.

Expected outcome: To develop a clinical tool to assist clinicians in the process of treatment decision-making in eTNBC, in order to maximize patient's benefit and quality of life, while minimizing AEs and financial burden to the health system.

Study Timeline

• Study Start: 2023-01-13
• Study First Submitted: 2023-05-08
• Status Verified: 2023-06
• Study First Submitted QC: 2023-06-20
• Last Update Submitted: 2023-06-20
• Study First Posted: 2023-06-23
• Last Update Posted: 2023-06-23
• Primary Completion: 2026-12
• Study Completion: 2029-12

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• Histologically documented TNBC (negative human epidermal growth factor receptor 2 [HER2], estrogen receptor [ER], and progesterone receptor [PgR] status)
• Stage 2 - 3 defined by the American Joint Committee of Cancer (AJCC) staging criteria 8th edition for breast cancer as assessed by the investigator based on radiological and/or clinical assessment
• Patient is a candidate to receive NACT with or without ICI as assessed by the investigator
• Patient is ≥ 18 years old at the time of consent to participate in this trial

Exclusion Criteria

• Metastatic disease on imaging (stage 4)

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Cohort A	Chemotherapy	Pembrolizumab + neoadjuvant chemotherapy
Cohort B	PBMCs phenotyping	Neoadjuvant chemotherapy
Cohort A	Whole Genome Sequencing	Pembrolizumab + neoadjuvant chemotherapy
Cohort A	ctDNA analysis	Pembrolizumab + neoadjuvant chemotherapy
Cohort A	Microbiome analysis	Pembrolizumab + neoadjuvant chemotherapy
Cohort A	TCR-β repertoire sequencing	Pembrolizumab + neoadjuvant chemotherapy
Cohort A	PBMCs phenotyping	Pembrolizumab + neoadjuvant chemotherapy
Cohort A	RNA-Sequencing	Pembrolizumab + neoadjuvant chemotherapy
Cohort B	ctDNA analysis	Neoadjuvant chemotherapy
Cohort B	Whole Genome Sequencing	Neoadjuvant chemotherapy
Cohort B	RNA-Sequencing	Neoadjuvant chemotherapy
Cohort B	Microbiome analysis	Neoadjuvant chemotherapy
Cohort B	TCR-β repertoire sequencing	Neoadjuvant chemotherapy
Cohort B	Chemotherapy	Neoadjuvant chemotherapy
Cohort A	Pembrolizumab	Pembrolizumab + neoadjuvant chemotherapy

Primary Outcome Measures

Name	Time	Method
Event-free survival (EFS)	Up to approximately 60 months	EFS is defined as the time from the start of neoadjuvant treatment to any of the following events: progression of disease that precludes surgery, local or distant recurrence, second primary malignancy (breast or other cancers) or death due to any cause
Overall survival (OS)	Up to approximately 60 months	OS is defined as the time from starting neoadjuvant treatment until death due to any cause
Identification of biomarkers to predict clinical outcomes (pCR at definitive surgery, EFS, OS).	After all data are analyzed, up to approximately 60 months	The clinical data (pCR at definitive surgery, EFS, OS) will be integrated with the results from the multiomics platform and multivariate predictive models of response to neoadjuvant chemotherapy (NACT) + immune checkpoint inhibitor (ICI) will be explored. Precisely, the multiomics platform will analyze: 1. RNA-Sequencing of the initial tumor and residual disease (if present); 2. microbiome analysis of the saliva and feces,; 3. circulating tumor DNA (ctDNA) analysis (targeted gene panel and shallow WGS),; 4. Tissue immune phenotyping,; 5. T-cell receptor beta (TCR-β) repertoire sequencing and analysis using ImmunoSeq hsTCRβ kit and immunoSEQ,; 6. Breast MRI imaging (before and after NACT),; Multiple algorithms including Multiple Kernel Learning, Multi-Omics Factor Analysis (MOFA) and Method for the Functional Integration of Spatial and Temporal Omics data (MEFISTO) will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs.
Pathologic complete response (pCR) rate at definitive surgery	after neoadjuvant treatment and surgery, up to approximately 27-30 weeks	The rate (given as a percentage) of patients with a pCR at definitive surgery using the definition of ypT0/Tis ypN0 (i.e., no invasive residual in breast or nodes; noninvasive breast residuals allowed) from the American Joint Committee on Cancer (AJCC) staging criteria

Trial Locations

Locations (1)

Vall d'Hebron Institute of Oncology; 🇪🇸 Barcelona, Spain